In this paper we compare two segmentation techniques, a parameter-free variant of the watershed algorithm and a new robust method based on adaptive contours. To test them, we use a set of fluorescence in-situ hybridisation images of leucocyte nuclei: these images were obtained in realistic conditions of mass screening, and do not meet the prerequisites of usual segmentation methods. We present ...

ÐThis paper addresses the problem of spatio-temporal segmentation of video sequences. An initial intensity segmentation method (watershed segmentation) provides a number of initial segments which are subsequently labeled, with a known number of labels, according to motion information. The label field is modeled as a Markov Random Field where the statistical spatial and temporal interactions are...

Mammograms are the soft X-rays meant for the detection of any lesions or cysts in breasts. Nowadays it is playing major role in the detection of breast cancer at an early stage. In this paper we have developed a computer aided diagnosis tool using MATLAB for breast cancer in Mamograms. This segmentation technique is based on the extraction of catchments basins through a topographic representati...

Image segmentation is one of the most common steps in digital image processing. The area many image segmentation algorithms (e.g., thresholding, edge detection, and region growing) employed for classifying a digital image into different segments. In this connection, finding a suitable algorithm for medical image segmentation is a challenging task due to mainly the noise, low contrast, and steep...

The use of Image Processing techniques in the field of bio-medical imaging is well known. This paper is an attempt to use image processing algorithms for the enhancing and highlighting suspicious areas in mammogram images for breast cancer detection. An image segmentation method based on morphological watershed transform has been developed. It is based on extraction of watershed lines from a to...

Watershed is one of the most popular tool defined by mathematical morphology. The algorithms which implement the watershed transform generally produce an over segmentation which includes the right image’s boundaries. Based on this last assumption, the segmentation problem turns out to be equivalent to a proper valuation of the saliency of each contour. Using such a measure, hierarchical watersh...

The watershed based cell reconstruction is a common approach to segment the cell system of foams and polycrystals. To avoid segmentation errors, a proper parametrisation of the algorithm is necessary. In this work, we propose a marker based method whose parameters are automatically adapted to the observed structure. The result is a nearly perfect cell reconstruction with segmentation errors bel...

We perform image segmentation using the Watershed algorithm, and then propose an implementation to run several image segmentation tasks on parallel using RADICAL-Pilot’s API. Apparently, we conducted some experiments to characterize the performance of our application, and found the results to be very encouraging.

Segmentation of medical images is very important nowadays since the images for diagnosis by Radiologist are huge in number. In this paper, texture based segmentation algorithms are considered for comparison. The problem with some of these methods is, they need human interaction for accurate and reliable segmentation. Segmentation based on Gray level co-occurrence matrix gives better result for ...